&lt;title&gt;Detection and correction of geometric distortion in 3D MR images&lt;/title&gt;

Breeuwer, Marcel; Holden, Mark P.; Zylka, Waldemar

doi:10.1117/12.430986

Cited by 32 publications

(38 citation statements)

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“…For a complete mapping of geometric distortion in MRI, a three-dimensional (3D) structure is required to enable defining reference features in three dimensions. There have been few reports of mapping of geometric distortion in 3D [2,10,11]. Breeuwer et al described [11] a spherical phantom consisting of a 3D array of 427 spherical reference structures at positions with a manufacturing error of less than 0.05 mm.…”

Section: Introductionmentioning

confidence: 99%

“…There have been few reports of mapping of geometric distortion in 3D [2,10,11]. Breeuwer et al described [11] a spherical phantom consisting of a 3D array of 427 spherical reference structures at positions with a manufacturing error of less than 0.05 mm. The size of the spheres was 11mm in diameter, which put a limit on the number of spheres that could be arranged in the phantom.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Geometric Distortion in Six Clinical Scanners Using a 3D-Printed Grid Phantom

Jafar

Dean

et al. 2017

J. Imaging

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A cost-effective regularly structured three-dimensional (3D) printed grid phantom was developed to enable the quantification of machine-related magnetic resonance (MR) distortion. This phantom contains reference features, "point-like" objects, or vertices, which resulted from the intersection of mesh edges in 3D space. 3D distortions maps were computed by comparing the locations of corresponding features in both MR and computer tomography (CT) data sets using normalized cross correlation. Results are reported for six MRI scanners at both 1.5 T and 3.0 T field strengths within our institution. Mean Euclidean distance error for all MR volumes in this study, was less than 2 mm. The maximum detected error for the six scanners ranged from 2.4 mm to 6.9 mm. The conclusions in this study agree well with previous studies that indicated that MRI is quite accurate near the centre of the field but is more spatially inaccurate toward the edges of the magnetic field.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Geometric Distortion in Six Clinical Scanners Using a 3D-Printed Grid Phantom

Jafar

Dean

et al. 2017

J. Imaging

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“…Any residual distortion measured in the corrected images can then be used as an overall measure of the accuracy. This method has also been used by previous investigators [13].…”

Section: Methods Of Validationmentioning

confidence: 95%

“…However, the possibility of geometric distortion being present in MR images still limits its full potential of use when high geometric accuracy is required. A lot of authors [11][12][13][14][15] have described distortion characteristics and correction methods in MR images, but there is no evidence that distortion correction has been really practiced in clinical routine. The geometric accuracy of the MR images is limited by the system itself and object induced distortions [11,12].…”

Section: Introductionmentioning

confidence: 98%

Correction of images in an open-configuration MR imaging system for radiation therapy planning and Interventional MRI

et al. 2008

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Purpose In this paper, we present a method to remove system induced geometric distortions in MR images. Methods A large 3D phantom with spherical balls was used to characterize geometric distortion on an AIRIS Mate 0.2 T MR Scanner (Hitachi). MR images of the phantom were acquired in axial, sagittal planes. Using 2D Fast Spin Echo (FSE) sequence, distortions were measured at each control point. Two piecewise interpolation methods were then applied to correct distortions and greyvalues. Results The distortion was reduced from 16 to 1.2 mm at 180 mm from the magnet center. Conclusion Distortions were characterized and corrected in any axial, sagittal or coronal slice within an effective FOV of 330(LR) × 180(AP) × 210(HF) mm 3 . A fast and accurate method for correction of geometric distortion was performed within large distances from the magnet isocenter.

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“…Usually, this parameter is very small and it is often neglected. However, it may be identified, since in some circumstances, it may decrease the registration accuracy as it is for MRI [4]. In the rest of the paper, this parameter will be neglected.…”

Section: The Imaging Modelmentioning

confidence: 99%

Pose Estimation and Feature Tracking for Robot Assisted Surgery with Medical Imaging

Doignon

Nageotte

Maurin³

et al. 2008

Lecture Notes in Electrical Engineering

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<title>Detection and correction of geometric distortion in 3D MR images</title>

Cited by 32 publications

References 0 publications

Assessment of Geometric Distortion in Six Clinical Scanners Using a 3D-Printed Grid Phantom

Assessment of Geometric Distortion in Six Clinical Scanners Using a 3D-Printed Grid Phantom

Correction of images in an open-configuration MR imaging system for radiation therapy planning and Interventional MRI

Pose Estimation and Feature Tracking for Robot Assisted Surgery with Medical Imaging

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